By Keith Black, PhD, CFA, CAIA, FDP | Managing Director, Content Strategy at CAIA Association
Recently, CAIA Association sat down for a conversation with Guen Donde, the Head of Research for the Institute of Business Ethics (IBE). Life moves pretty fast in the world of GDPR, big data, and artificial intelligence. If you don’t stop and look around once in a while you could miss it. Here are a few of the takeaways from our conversation—don’t miss the full interview at the end of this synopsis.
While doing business ethically reduces risks and is the right thing to do, ethics are not always top of mind for financial market professionals. In fact, unfortunately, when it comes to ethical lapses, the financial sector seems to be more frequently cited in the media than most others.
Some people treat ethics in a negative or exclusionary manner. For example, the question asked isn’t “What are we going to do?”, but “What aren’t we going to do?” When viewed this way, the intersection of finance and technology initially seems to codify the biases found in human behavior. The concerns are so strong that a new book “The Ethical Algorithm” by Kearns and Roth explores how human biases and outright manipulation have found their way into artificial intelligence algorithms. The data scientists building those algorithms are encouraged to understand their own biases to ensure that they aren’t codified into systems that control trading and credit-granting decisions.
How fast is life moving in this area? A good indicator is that, despite laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act, tech giants are literally begging for regulators to place guardrails around their own ethical behavior. It almost seems that, without further regulation, tech companies are expressing a need or a want to operate in ethical gray areas in order to not fall behind their competitors. IBE research on GDPR states that regulation is just the beginning of the conversation and that ethical standards should go above and beyond the law. It is sad that laws are necessary to prevent behavior that should be avoided simply with common sense and personal morality.
The compliance departments of many firms, whether in the financial sector or elsewhere, are increasingly building codes of ethics that extend to data and the way the firm interacts with markets, consumers, and technology. But codes of ethics and ethical behavior have to be implemented across the organization, not just in the compliance department. Everyone in the organization needs to think about how they use data and to be aware of how to report and prevent ethical violations. The compliance department, then, is charged with communicating the policies and training their entire firm. Training is most effective when team members are asked to consider how they would react when faced with a specific scenario. Of course, top leadership needs to be included in the training and conduct themselves in a way that sets the tone for the rest of the organization to follow suit. Finally, data ethics don’t belong just in the information technology department. The board needs to have the ultimate accountability to build structures and a management team that direct IT efforts in an organized, productive, and ethical fashion.
No education, especially in financial data science, is complete without a grounding in ethical principles. The FDP exams use these three readings from IBE as its ethical foundation. Of course, these guidelines are only a minimum as financial market participants are encouraged to do the right thing, even when no one is looking. Oh yeah!
Keith Black, PhD, CFA, CAIA, FDP is Managing Director of Content Strategy at CAIA Association. Follow him on Twitter and LinkedIn.
To hear the full interview, see the link to archived webinar here.
To find the schedule for future FDP webinars, see here.
More information on the FDP exam can be found here.
To access the research discussed on the webcast, use the links below:
Beyond Law: Ethical Culture and GDPR
Business Ethics and Artificial Intelligence